On Thursday (19th June), Mats Kindahl and I will be presenting a free webinar on why and how you should be using MySQL Fabric to add Sharding (scaling out reads & writes) and High Availability to MySQL. This product has only recently gone GA and so this is a good chance to discover it’s for you and to get your questions answered by the people who wrote the software! All you need to do is register for the MySQL Fabric webinar here.

Abstract

MySQL Fabric is built around an extensible and open source framework for managing farms of MySQL Servers. Currently two features have been implemented – High Availability (built on top of MySQL Replication) and scaling out using …

Download MariaDB 10.0.12

Release Notes Changelog What is MariaDB 10.0?

MariaDB APT and YUM Repository Configuration Generator

The MariaDB project is pleased to announce the immediate availability of MariaDB 10.0.12. This is a Stable (GA) release.

See the Release Notes and …

We had really great webinar on Replicating to/from Oracle earliest this month, and you can view the recording of that Webinar here.

A good sign of how great a Webinar was is the questions that come afterwards, and we didn’t get through them all. so here are all the questions and answers for the entire webinar.

Q: What is the overhead of Replicator on source database with asynchronous CDC?

A: With asynchronous operation there is no substantial CPU overhead (as with synchronous), but the amount of generated redo logs becomes bigger requiring more disk space and better log management to ensure that the space is used effectively.

Q: Do you support migration from Solaris/Oracle to Linux/Oracle?

A: The replication is not certified for use on Solaris, however, it is possible to …

I have just released version 3.5.5 of MyQuery, which is a minor feature, cleanup and bugfix release. If you don't know MyQuery since before, this is an Open-Source Windows based MySQL and MariaDB ad-hoc query tool. What makes MyQuery slightly different from all the other similar tools is that MyQuery has a focus on SQL-scripting, allowing statements in a script to be run one at the time, to restart a script where it left of in the case of an error and some other features like this. MyQuery features colour coded syntax as it uses Scintilla for editing, and this is highly configurable. Also, multiple editing tabs are supported. Another thing that makes MyQuery stand out a bit is that it is highly flexible. If you have SQL statements that you run often to monitor the state of the server or your application, then it is real easy to implement this as a simple tool accessible from the MyQuery menu.

There …

In the latest release of MySQL Utilities 1.4.3 GA, the performance of the mysqldbcompare utility has been considerably improved along with some bug fixes. This blog briefly explains some of the improvements that were made and shows evidence of the increased performance of database comparison.

• A new step was added to the data consistency check. It now executes a full table checksum, which is faster when no differences are expected. The algorithm to find row differences is only executed if this preliminary table
  checksum fails.

• A new --skip-checksum-table option was added to skip this new step should you wish to (when you know there are differences it saves a bit of time).

• The current algorithm to find row differences was optimized to internally store and access the generated hash values.

What follows are some examples comparing the world database with …

June 16, 2014 By Severalnines

MongoDB is great at storing clickstream data, but using it to analyze millions of documents can be challenging. Hadoop provides a way of processing and analyzing data at large scale. Since it is a parallel system, workloads can be split on multiple nodes and computations on large datasets can be done in relatively short timeframes. MongoDB data can be moved into Hadoop using ETL tools like Talend or Pentaho Data Integration (Kettle).

In this blog, we’ll show you how to integrate your MongoDB and Hadoop datastores using Talend. We have a MongoDB database collecting clickstream data from several websites. We’ll create a job in Talend to extract the documents from MongoDB, transform and then load them into HDFS. We will also show you how to schedule this job to be executed every 5 minutes.

Test Case

We have an application …

Before you start creating database entities, spend some time designing your database to ensure that it is fit for your purpose. The time you invest in this process saves a lot of time and trouble later. Professional database designers fine-tune their design using a process called 'normalization'. The normalization process takes your database design through a number of 'normal forms', which aim to ensure efficient data access, greater query flexibility, and easier maintenance.

For example, the First Normal Form (or '1NF') ensures that all your database columns contain only a single value. A column that contains multiple data values is difficult to access and keep up to date. It also ensures that each table row only represents a single 'real world' item. Like all the other normal forms, this encourages you to split your data across multiple tables, with less rows in each table. You can quickly see the benefits of this approach as your database …

MariaDB Roadshow Helsinki

One could say that MariaDB originates from Finland’s capital Helsinki. In fact so does MySQL. It was in the Helsinki area that MySQL saw daylight. It was here that Monty Widenius laid the ground for MySQL already in the 80’s, maybe even 1979, when he created UNIREG from which parts were reused when he together with the other 2 founders of MySQL released the first version of MySQL in 1995.

Last week, 19 years later, a MariaDB event was held in Helsinki. It was SkySQL that arranged the first in a row of this year’s MariaDB Roadshow events. The agenda included a walkthrough of MariaDB 10.0, some roadmap and MariaDB high availability options, which consisted of MariaDB Galera Cluster and …

While working with an error that my students surfaced in the Oracle Database 12c, I blogged about the limit of using a subquery in an Oracle INSERT statement, and I discovered something when retesting it in MySQL. It was a different limitation. I was also surprised when I didn’t find any mention of it through a Google search, but then I may just not have the right keywords.

The original test case uses a subquery to create a multiple row result set for an INSERT statement. Unfortunately, I discovered that you can’t always embed a UNION or UNION ALL inside a subquery. At least, you can’t when you call the subquery inside an INSERT statement. For example, let’s create a DESTINATION table and then we’ll try to insert records with a query that …

The development version of PECL/mysqlnd_ms now has an very early version of distributed (2PC/XA) transaction support tailored for use with clusters of MySQL servers. XA transactions can span multiple servers in a cluster to ensure transaction guarantees among them. In real life, there is always, at some point, a sequence of work on your data for which atomicity, consistency, isolation, and durability must be given. The early generation of NoSQL sharding solutions has a weak spot here. How do you, as a developer, ensure a logical operation affecting two shards is either applied to both or none? Either you don’t …